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  4. A Spectrally Efficient MIMO System with Sparse Matrix Precoding

A Spectrally Efficient MIMO System with Sparse Matrix Precoding

Files

202115007.pdf (1.32 MB)

Date

2023

Authors

Yadav, Prabhanshu

Journal Title

Journal ISSN

Volume Title

Publisher

Dhirubhai Ambani Institute of Information and Communication Technology

Abstract

This thesis proposes a novel technique of sparse matrix-based precoding at thetransmitter of a Multiple Input Multiple Output (MIMO) system. We proposedtwo sparse matrix precoded MIMO systems. Our first proposal improves thespectral efficiency beyond the existing spectral efficiency of Precoding-aided SpatialModulation (PSM-MIMO) system. Our second proposal increases spectralefficiency compared to an existing MIMO system.Both proposals use a two-stage precoding approach in which the conventionalzero-forcing (ZF) MIMO precoder, which inverts the matrix MIMO channel, iscombined with a sparse matrix precoding. With the conventional ZF precoder, thedegrees of freedom (DoF) available at the transmitter equals the number of antennasat the receiver. By adding another layer of precoding using a sparse matrix,we increase the DoF at the transmitter, thereby facilitating an increase in spectralefficiency. We demonstrate proof of the concept (PoC) by simulation-driven experiments.Our PoC is based on the ML (Maximum Likelihood) detection at thereceiver. ML detection has quite high complexity. We propose a belief propagationalgorithm at the receiver which is more practical to implement in a real-worldsystem. The belief propagation algorithm leverages the sparseness of the precodingmatrix and has low computational complexity.

Description

Keywords

SMP-MIMO, SMP-PSM-MIMO, spectral efficiency, zero-forcing precoder, ML Detector, LDPC, belief propagation

Citation

Yadav, Prabhanshu (2023). A Spectrally Efficient MIMO System with Sparse Matrix Precoding. Dhirubhai Ambani Institute of Information and Communication Technology. vii, 51 p. (Acc. # T01150).

URI

http://ir.daiict.ac.in/handle/123456789/1207

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M Tech (EC) Dissertations

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